Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. An electronic device comprising: one or more processors; and one or more computer-readable media storing instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising: receiving first image data representing a first image; receiving second image data representing a second image; determining a first region of the first image; determining a second region of the second image; determining a difference between a Discrete Cosine Transform (DCT) coefficient of the first region and a DCT coefficient of the second region; based at least in part on the difference, assigning the first region of the first image as either a background or a foreground and assigning the second region of the second image as the other of the background or the foreground; and correcting a defect in the first image or the second image based at least in part on whether the first image is assigned as the background or the foreground.
An electronic device, such as an image capture device, is designed to enhance images. It includes processors and memory storing instructions to perform image processing. The device receives two distinct sets of image data, a first image and a second image. It identifies a specific region within each image. It then calculates the difference between the Discrete Cosine Transform (DCT) coefficients of these two regions. Based on this difference, the device classifies the first region as either foreground or background, and the second region as the opposite. Finally, it corrects a defect in either the first or second image, with the type of correction depending on whether the first image was classified as foreground or background.
2. The electronic device as recited in claim 1 , the operations further comprising: determining that the first region of the first image comprises a first depiction of at least a portion of a face; and determining that the second region of the second image comprises a second depiction of at least the portion of the face.
An electronic device, such as an image capture device, is designed to enhance images. It includes processors and memory storing instructions to perform image processing. The device receives two distinct sets of image data, a first image and a second image. It identifies a specific region within each image and calculates the difference between their Discrete Cosine Transform (DCT) coefficients. Based on this difference, the device classifies the first region as either foreground or background, and the second region as the opposite. It then corrects a defect in either image based on this classification. A specific application of this involves the device determining that the identified first region in the first image contains a depiction of a portion of a face, and similarly, the second region in the second image also contains a depiction of that same portion of the face.
3. The electronic device as recited in claim 1 , the operations further comprising: generating third image data representing a third image by at least replacing the first region of the first image with the second region of the second image; receiving fourth image data representing a fourth image; determining a third region of the fourth image; and based at least in part on a difference between the second region and the third region, selecting the second region of the second image for generating the third image data.
An electronic device, such as an image capture device, is designed to enhance images. It includes processors and memory storing instructions to perform image processing. The device receives two distinct sets of image data, a first image and a second image. It identifies a specific region within each image and calculates the difference between their Discrete Cosine Transform (DCT) coefficients. Based on this difference, the device classifies the first region as either foreground or background, and the second region as the opposite. It then corrects a defect in either image based on this classification. Furthermore, the device generates a third image by replacing the first identified region in the first image with the second identified region from the second image. To make this replacement decision, the device also receives a fourth image and identifies a third region within it. It then selects the second region from the second image for replacement, based on a comparison between the second region and this third region from the fourth image.
4. The electronic device as recited in claim 1 , the operations further comprising: determining that the second region comprises a more desirable depiction of an object than a depiction of the object in the first region; and determining to replace the first region of the first image with the second region of the second image based at least in part on the second region comprising the more desirable depiction of the object relative to the first region.
An electronic device, such as an image capture device, is designed to enhance images. It includes processors and memory storing instructions to perform image processing. The device receives two distinct sets of image data, a first image and a second image. It identifies a specific region within each image and calculates the difference between their Discrete Cosine Transform (DCT) coefficients. Based on this difference, the device classifies the first region as either foreground or background, and the second region as the opposite. It then corrects a defect in either image based on this classification. Specifically, the device determines that the second region contains a more desirable depiction of an object compared to the depiction of the same object in the first region. Based on this determination of greater desirability, the device decides to replace the first region of the first image with the second region of the second image as part of its defect correction.
5. The electronic device as recited in claim 1 , the operations further comprising: determining that the first region is associated with a sensor defect; and determining that the second region is not associated with the sensor defect, and wherein correcting the defect in the first image or the second image is further based at least in part on the first region being associated with the sensor defect and the second region not being associated with the sensor defect.
An electronic device, such as an image capture device, is designed to enhance images. It includes processors and memory storing instructions to perform image processing. The device receives two distinct sets of image data, a first image and a second image. It identifies a specific region within each image and calculates the difference between their Discrete Cosine Transform (DCT) coefficients. Based on this difference, the device classifies the first region as either foreground or background, and the second region as the opposite. It then corrects a defect in either image based on this classification. This defect correction is specifically informed by the device determining that the first region is associated with a sensor defect, while the second region is not. The presence of the defect in the first region and its absence in the second are key factors in how the defect is corrected.
6. The electronic device as recited in claim 1 , the operations further comprising: storing fourth image data representing a fourth image, the fourth image depicting an undesirable depiction of an object; analyzing the first image data using at least the fourth image data; and based at least in part on analyzing the first image data, determining that the first region of the first image includes the first undesirable depiction of the object.
An electronic device, such as an image capture device, is designed to enhance images. It includes processors and memory storing instructions to perform image processing. The device receives two distinct sets of image data, a first image and a second image. It identifies a specific region within each image and calculates the difference between their Discrete Cosine Transform (DCT) coefficients. Based on this difference, the device classifies the first region as either foreground or background, and the second region as the opposite. It then corrects a defect in either image based on this classification. To identify defects, the device stores a fourth image that depicts an undesirable object. It then analyzes the first image data using this stored fourth image. Based on this analysis, the device determines that the first identified region of the first image contains an undesirable depiction of an object.
7. The electronic device as recited in claim 1 , further comprising: analyzing the first region of the first image using at least one of shape analysis or color analysis; and based at least in part on analyzing the first region of the first image, determining that the first region of the first image includes an undesirable depiction of an object, and wherein correcting the defect in the first image or the second image is further based at least in part on the first image including the undesirable depiction of the object.
An electronic device, such as an image capture device, is designed to enhance images. It includes processors and memory storing instructions to perform image processing. The device receives two distinct sets of image data, a first image and a second image. It identifies a specific region within each image and calculates the difference between their Discrete Cosine Transform (DCT) coefficients. Based on this difference, the device classifies the first region as either foreground or background, and the second region as the opposite. It then corrects a defect in either image based on this classification. The device further analyzes the first region of the first image using techniques like shape analysis or color analysis. Based on this analysis, it determines that the first region contains an undesirable depiction of an object. This finding that the first image includes an undesirable object depiction is an additional factor in how the defect in either image is corrected.
8. The electronic device as recited in claim 1 , wherein: the first image data is generated by a camera, the first image depicting a scene that includes an object; the second image data is generated by the camera, the second image depicting at least a portion of the scene including the object; and the second image data is generated by the camera within a first period of time before the first image data or within a second period of time after the first image data.
An electronic device, such as an image capture device, is designed to enhance images. It includes processors and memory storing instructions to perform image processing. The device receives two distinct sets of image data, a first image and a second image. It identifies a specific region within each image and calculates the difference between their Discrete Cosine Transform (DCT) coefficients. Based on this difference, the device classifies the first region as either foreground or background, and the second region as the opposite. It then corrects a defect in either image based on this classification. In this specific configuration, both the first and second images are captured by the *same camera*. The first image depicts a scene with an object, and the second image depicts at least a portion of that same scene including the object. Crucially, the second image is captured within a short period either just before or just after the first image.
9. The electronic device as recited in claim 1 , wherein the first image data includes a first resolution and the second image data includes a second resolution, the first resolution being different than the second resolution.
An electronic device, such as an image capture device, is designed to enhance images. It includes processors and memory storing instructions to perform image processing. The device receives two distinct sets of image data, a first image and a second image. It identifies a specific region within each image and calculates the difference between their Discrete Cosine Transform (DCT) coefficients. Based on this difference, the device classifies the first region as either foreground or background, and the second region as the opposite. It then corrects a defect in either image based on this classification. A unique aspect is that the first image data has a different resolution compared to the second image data.
10. A method comprising: receiving first image data representing a first image, the first image depicting at least a scene that includes an object; receiving second image data representing a second image, the second image depicting at least a portion of the scene that includes the object; determining that a first region of the first image includes a first depiction of the object; determining that a second region of the second image includes a second depiction of the object; determining a difference between a Discrete Cosine Transform (DCT) coefficient of the first region and a DCT coefficient of the second region; based at least in part on the difference, assigning the first region of the first image as either a background or a foreground and assigning the second region of the second image as the other of the background or the foreground; and based at least in part on whether the first image is assigned as the background or the foreground, generating third image data representing a third image by at least replacing the first region of the first image with the second region of the second image.
A method for enhancing images involves several steps. First, it receives first image data representing a first image that depicts a scene including an object. Concurrently or nearly concurrently, it receives second image data representing a second image that also depicts at least a portion of the same scene and object. The method then identifies a specific first region within the first image that contains a depiction of the object and a second region within the second image that also contains a depiction of the object. It calculates the difference between the Discrete Cosine Transform (DCT) coefficients of these two identified regions. Based on this difference, the method assigns the first region of the first image as either a background or a foreground, and consequently, assigns the second region of the second image as the other classification. Finally, based on this background/foreground assignment, the method generates third image data representing a third, enhanced image by replacing the first region of the first image with the second region of the second image.
11. The method as recited in claim 10 , wherein: determining that the first region of the first image includes the first depiction of the object comprises determining that the first region of the first image depicts at least a portion of a face, the at least the portion of the face including the object; and determining that the second region of the second image includes the second depiction of the object comprises determining that the second region of the second image depicts at least the portion of the face.
A method for enhancing images involves several steps. It receives first image data (first image, scene with object) and second image data (second image, portion of scene with object). It identifies a first region in the first image and a second region in the second image, both depicting the object. It calculates the difference between their Discrete Cosine Transform (DCT) coefficients and, based on this, assigns the regions as foreground or background. Then, based on this assignment, it generates a third image by replacing the first region with the second. Specifically, in this method, determining that the first region includes the first depiction of the object means detecting that the first region depicts at least a portion of a face. Similarly, determining that the second region includes the second depiction of the object means detecting that the second region also depicts at least the same portion of the face.
12. The method as recited in claim 10 , further comprising: receiving fourth image data representing a fourth image; determining that a third region of the fourth image includes a third depiction of the object; and based at least in part on the second depiction and the third depiction, selecting the second region of the second image for generating the third image data.
A method for enhancing images involves several steps. It receives first image data (first image, scene with object) and second image data (second image, portion of scene with object). It identifies a first region in the first image and a second region in the second image, both depicting the object. It calculates the difference between their Discrete Cosine Transform (DCT) coefficients and, based on this, assigns the regions as foreground or background. Then, based on this assignment, it generates a third image by replacing the first region with the second. Additionally, this method receives fourth image data representing a fourth image. It then determines that a third region within this fourth image includes a third depiction of the object. Finally, it selects the second region of the second image for generating the third image data based on a comparison between the second depiction of the object and this third depiction from the fourth image.
13. The method as recited in claim 10 , further comprising: determining that the second depiction of the object includes a more desirable depiction of the object than the first depiction of the object, and wherein generating the third image data representing the third image is based at least in part on the second depiction of the object including the more desirable depiction of the object.
A method for enhancing images involves several steps. It receives first image data (first image, scene with object) and second image data (second image, portion of scene with object). It identifies a first region in the first image and a second region in the second image, both depicting the object. It calculates the difference between their Discrete Cosine Transform (DCT) coefficients and, based on this, assigns the regions as foreground or background. Then, based on this assignment, it generates a third image by replacing the first region with the second. A key aspect of this method is determining that the second depiction of the object in the second image is *more desirable* than the first depiction of the object in the first image. The generation of the third image, by replacing the first region, is specifically based on this determination that the second depiction offers a more desirable representation of the object.
14. The method as recited in claim 10 , further comprising: determining that the first depiction of the object is associated with a sensor defect; and determining that the second depiction of the object is not associated with the sensor defect, and wherein generating the third image data representing the third image is based at least in part on the first depiction of the object being associated with the sensor defect and the second depiction of the object not being associated with the sensor defect.
A method for enhancing images involves several steps. It receives first image data (first image, scene with object) and second image data (second image, portion of scene with object). It identifies a first region in the first image and a second region in the second image, both depicting the object. It calculates the difference between their Discrete Cosine Transform (DCT) coefficients and, based on this, assigns the regions as foreground or background. Then, based on this assignment, it generates a third image by replacing the first region with the second. This method also involves determining that the first depiction of the object is associated with a sensor defect, while the second depiction of the object is *not* associated with a sensor defect. The process of generating the third image, specifically by replacing the first region, is directly based on these findings about the presence or absence of a sensor defect in each depiction.
15. The method as recited in claim 10 , wherein determining that the first region includes the first depiction of the object comprises at least: storing fourth image data representing a fourth image, the fourth image depicting an undesirable depiction of an additional object, the additional object including a similar object to the object; analyzing the first image data using at least the fourth image data; and based at least in part on analyzing the first image data, determining that the first region of the first image includes the first depiction of the object.
A method for enhancing images involves several steps. It receives first image data (first image, scene with object) and second image data (second image, portion of scene with object). It identifies a first region in the first image and a second region in the second image, both depicting the object. It calculates the difference between their Discrete Cosine Transform (DCT) coefficients and, based on this, assigns the regions as foreground or background. Then, based on this assignment, it generates a third image by replacing the first region with the second. The specific way the method determines that the first region includes the first depiction of the object involves storing fourth image data that depicts an undesirable representation of an object similar to the main object. It then analyzes the first image data by comparing it with this stored fourth image data. Based on this comparison, it identifies the first depiction of the object within the first region of the first image.
16. The method as recited in claim 10 , further comprising: analyzing the first region of the first image using at least one of shape analysis or color analysis; and based at least in part on analyzing the first region of the first image, determining that the first region of the first image includes an undesirable depiction of the object, and wherein determining to replace the first region of the first image with the second region of the second image is further based at least in part on the first image including the undesirable depiction of the object.
A method for enhancing images involves several steps. It receives first image data (first image, scene with object) and second image data (second image, portion of scene with object). It identifies a first region in the first image and a second region in the second image, both depicting the object. It calculates the difference between their Discrete Cosine Transform (DCT) coefficients and, based on this, assigns the regions as foreground or background. Then, based on this assignment, it generates a third image by replacing the first region with the second. This method further involves analyzing the first region of the first image using techniques such as shape analysis or color analysis. Based on this analysis, it determines that the first region contains an undesirable depiction of the object. The decision to replace the first region of the first image with the second region of the second image is further based on this finding that the first image includes the undesirable depiction of the object.
17. The method as recited in claim 10 , further comprising: detecting a first input associated with a button being depressed a first distance; based at least in part on detecting the first input, generating, using a camera, the first image data representing the first image; detecting a second input associated with the button being depressed a second distance; and based at least in part on the second input, generating, using the camera, the second image data representing the second image.
A method for enhancing images involves several steps. It receives first image data (first image, scene with object) and second image data (second image, portion of scene with object). It identifies a first region in the first image and a second region in the second image, both depicting the object. It calculates the difference between their Discrete Cosine Transform (DCT) coefficients and, based on this, assigns the regions as foreground or background. Then, based on this assignment, it generates a third image by replacing the first region with the second. The method specifically obtains the image data by detecting a first input, such as a button being depressed a first distance, which triggers a camera to generate the first image data. Subsequently, it detects a second input, such as the same button being depressed a second, different distance, which triggers the camera to generate the second image data.
18. An electronic device comprising: one or more processors; and one or more computer-readable media storing instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising: receiving first image data representing a first image; receiving second image data representing a second image; determining a first region of the first image; determining a second region of the second image; determining a difference between a Discrete Cosine Transform (DCT) coefficient of the first region and a DCT coefficient of the second region; based at least in part on the difference, assigning the first region of the first image as either a background or a foreground and assigning the second region of the second image as the other of the background or the foreground; and determining to replace the first region of the first image with the second region of the second image, based at least in part on whether the first image is assigned as the background or the foreground.
An electronic device, such as an image capture device, is designed to facilitate image correction. It includes processors and memory storing instructions to perform image processing. The device receives two distinct sets of image data, a first image and a second image. It identifies a specific region within each image. It then calculates the difference between the Discrete Cosine Transform (DCT) coefficients of these two regions. Based on this difference, the device classifies the first region of the first image as either foreground or background, and the second region of the second image as the opposite classification. Finally, based on whether the first image was classified as background or foreground, the device determines that it should replace the first region of the first image with the second region of the second image.
19. The electronic device as recited in claim 18 , the operations further comprising generating third image data representing a third image by at least replacing the first region of the first image with the second region of the second image.
An electronic device, such as an image capture device, is designed to facilitate image correction. It includes processors and memory storing instructions to perform image processing. The device receives two distinct sets of image data, a first image and a second image. It identifies a specific region within each image and calculates the difference between their Discrete Cosine Transform (DCT) coefficients. Based on this difference, the device classifies the first region as either foreground or background, and the second region as the opposite. Based on this classification, the device determines that it should replace the first region of the first image with the second region of the second image. Following this determination, the device then proceeds to generate third image data, which represents a new third image, by performing the actual replacement of the first region of the first image with the second region of the second image.
20. The electronic device as recited in claim 19 , the operations further comprising: receiving third image data representing a third image; determining a third region of the third image; comparing the DCT coefficient of the second region and DCT coefficient of the third region; and determining, based at least in part on the comparing, the third image as a background image or a foreground image.
An electronic device, such as an image capture device, is designed to facilitate image correction. It includes processors and memory storing instructions to perform image processing. The device receives two distinct sets of image data, a first image and a second image. It identifies a specific region within each image and calculates the difference between their Discrete Cosine Transform (DCT) coefficients. Based on this difference, the device classifies the first region as either foreground or background, and the second region as the opposite. Based on this classification, the device determines that it should replace the first region of the first image with the second region of the second image, and then generates a third image by performing this replacement. Subsequently, the device receives *another* third image data and identifies a third region within it. It then compares the DCT coefficient of the second region from the initial second image with the DCT coefficient of this new third region. Based on this comparison, the device classifies this *another* third image as either a background image or a foreground image.
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August 4, 2020
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